Detrended fluctuation analysis (DFA) was introduced in early 1990s [1]}, [2]}, [3]} as a method for analyzing fractal properties of underlying data. The method was later majorly popularized in the long-range correlations [4]}, [5]} and multi-fractal analyses [6]}. Recently, DFA has been generalized for long-range cross-correlations analysis [7]}, [8]}, [9]}, [10]} as well as an examination of correlations between non-stationary series [11]}, [12]}. The method has been applied and utilized across wide range of disciplines ranging from physiology to cardiology, DNA analysis and neurology to (hydro)meteorology, economics and finance, engineering and environment and many others [13]}, [14]}, [15]}, [16]}, [17]}, [18]}, [19]}, [20]}, [21]}. Here, we propose a framework based on the detrended fluctuation analysis which allows for a regression analysis of possibly non-stationary and long-range dependent data at different scales.
